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Journal of Bioinformatics and Computational Biology

Dan Luo, Shu-Lin Wang, Jianwen Fang, Wei Zhang
MicroRNAs (miRNAs) play a key role in gene expression and regulation in various organisms. They control a wide range of biological processes and are involved in several types of cancers by causing mRNA degradation or translational inhibition. However, the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With the accumulation of the expression data of miRNAs and mRNAs, many computational methods have been proposed to predict miRNA-mRNA regulatory relationship. However, most existing methods require the number of modules predefined that may be difficult to determine beforehand...
December 28, 2017: Journal of Bioinformatics and Computational Biology
Vladimir Y Ovchinnikov, Denis V Antonets, Lyudmila F Gulyaeva
MicroRNAs (miRNAs) play important roles in the regulation of gene expression at the post-transcriptional level. Many exogenous compounds or xenobiotics may affect microRNA expression. It is a well-established fact that xenobiotics with planar structure like TCDD, benzo(a)pyrene (BP) can bind aryl hydrocarbon receptor (AhR) followed by its nuclear translocation and transcriptional activation of target genes. Another chemically diverse group of xenobiotics including phenobarbital, DDT, can activate the nuclear receptor CAR and in some cases estrogen receptors ESR1 and ESR2...
December 10, 2017: Journal of Bioinformatics and Computational Biology
Oleg V Vishnevsky, Andrey V Bocharnikov, Nikolay A Kolchanov
The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches...
December 10, 2017: Journal of Bioinformatics and Computational Biology
Oliver Eulenstein, Qin Ding, Hisham Al-Mubaid
No abstract text is available yet for this article.
December 7, 2017: Journal of Bioinformatics and Computational Biology
Jiang Xie, Dongfang Lu, Jiaxin Li, Jiao Wang, Yong Zhang, Yanhui Li, Qing Nie
Many major diseases, including various types of cancer, are increasingly threatening human health. However, the mechanisms of the dynamic processes underlying these diseases remain ambiguous. From the holistic perspective of systems science, complex biological networks can reveal biological phenomena. Changes among networks in different states influence the direction of living organisms. The identification of the kernel differential subgraph (KDS) that leads to drastic changes is critical. The existing studies contribute to the identification of a KDS in networks with the same nodes; however, networks in different states involve the disappearance of some nodes or the appearance of some new nodes...
December 4, 2017: Journal of Bioinformatics and Computational Biology
Olga Kiseleva, Ekaterina Poverennaya, Alexander Shargunov, Andrey Lisitsa
Proteomic challenges, stirred up by the advent of high-throughput technologies, produce large amount of MS data. Nowadays, the routine manual search does not satisfy the "speed" of modern science any longer. In our work, the necessity of single-thread analysis of bulky data emerged during interpretation of HepG2 proteome profiling results for proteoforms searching. We compared the contribution of each of the eight search engines (X!Tandem, MS-GF[Formula: see text], MS Amanda, MyriMatch, Comet, Tide, Andromeda, and OMSSA) integrated in an open-source graphical user interface SearchGUI ( http://searchgui...
November 13, 2017: Journal of Bioinformatics and Computational Biology
Abolfazl Rezvan, Changiz Eslahchi
A metabolic network model provides a computational framework for studying the metabolism of a cell at the system level. The organization of metabolic networks has been investigated in different studies. One of the organization aspects considered in these studies is the decomposition of a metabolic network. The decompositions produced by different methods are very different and there is no comprehensive evaluation framework to compare the results with each other. In this study, these methods are reviewed and compared in the first place...
November 13, 2017: Journal of Bioinformatics and Computational Biology
Fedor Kazantsev, Ilya Akberdin, Sergey Lashin, Natalia Ree, Vladimir Timonov, Alexander Ratushny, Tamara Khlebodarova, Vitaly Likhoshvai
MOTIVATION: Living systems have a complex hierarchical organization that can be viewed as a set of dynamically interacting subsystems. Thus, to simulate the internal nature and dynamics of the entire biological system, we should use the iterative way for a model reconstruction, which is a consistent composition and combination of its elementary subsystems. In accordance with this bottom-up approach, we have developed the MAthematical Models of bioMOlecular sysTems (MAMMOTh) tool that consists of the database containing manually curated MAMMOTh fitted to the experimental data and a software tool that provides their further integration...
November 3, 2017: Journal of Bioinformatics and Computational Biology
Debika Choudhury, Amit Agarwal, Supreet Saini
From the definition, it appears that phenotypic robustness and evolvability of an organism are inversely related to each other. However, a number of studies exploring this question have found conflicting evidences in this regard. This question motivated the current work where we explore the relationship between robustness and evolvability. As a model system, we pick the Feed Forward Loops (FFLs), and develop a framework to characterize their performance in terms of their ability to resist changes to steady state expression (robustness), and their ability to evolve towards novel phenotypes (evolvability)...
November 3, 2017: Journal of Bioinformatics and Computational Biology
(no author information available yet)
No abstract text is available yet for this article.
December 2017: Journal of Bioinformatics and Computational Biology
S Subasri, Santosh Kumar Chaudhary, K Sekar, Manish Kesherwani, D Velmurugan
Fumarase catalyzes the reversible, stereospecific hydration/dehydration of fumarate to L-malate during the Kreb's cycle. In the crystal structure of the tetrameric fumarase, it was found that some of the active site residues S145, T147, N188 G364 and H235 had water-mediated hydrogen bonding interactions with pyromellitic acid and citrate which help to the protonation state for the conversion of fumarate to malate. When His 235 is mutated with Asn (H235N), water-mediated interactions were lost due to the shifting of active site water molecule by 0...
December 2017: Journal of Bioinformatics and Computational Biology
Esaie Kuitche, Manuel Lafond, Aïda Ouangraoua
The architecture of eukaryotic coding genes allows the production of several different protein isoforms by genes. Current gene phylogeny reconstruction methods make use of a single protein product per gene, ignoring information on alternative protein isoforms. These methods often lead to inaccurate gene tree reconstructions that require to be corrected before phylogenetic analyses. Here, we propose a new approach for the reconstruction of gene trees and protein trees accounting for alternative protein isoforms...
October 19, 2017: Journal of Bioinformatics and Computational Biology
Soheila Montaseri, Fatemeh Zare-Mirakabad, Mohammad Ganjtabesh
Finding an effective measure to predict a more accurate RNA secondary structure is a challenging problem. In the last decade, an experimental method, known as selective [Formula: see text]-hydroxyl acylation analyzed by primer extension (SHAPE), was proposed to measure the tendency of forming a base pair for almost all nucleotides in an RNA sequence. These SHAPE reactivities are then utilized to improve the accuracy of RNA structure prediction. Due to a significant impact of SHAPE reactivity and in order to reduce the experimental costs, we propose a new model called HL-k-mer...
October 19, 2017: Journal of Bioinformatics and Computational Biology
Lu Liu, Jianhua Ruan
Chromatin conformation capture with high-throughput sequencing (Hi-C) is a powerful technique to detect genome-wide chromatin interactions. In this paper, we introduce two novel approaches to detect differentially interacting genomic regions between two Hi-C experiments using a network model. To make input data from multiple experiments comparable, we propose a normalization strategy guided by network topological properties. We then devise two measurements, using local and global connectivity information from the chromatin interaction networks, respectively, to assess the interaction differences between two experiments...
October 19, 2017: Journal of Bioinformatics and Computational Biology
Abdullah N Arslan, Jithendar Anandan, Eric Fry, Keith Monschke, Nitin Ganneboina, Jason Bowerman
Recently proposed relative addressing-based ([Formula: see text]) RNA secondary structure representation has important features by which an RNA structure database can be stored into a suffix array. A fast substructure search algorithm has been proposed based on binary search on this suffix array. Using this substructure search algorithm, we present a fast algorithm that finds the largest common substructure of given multiple RNA structures in [Formula: see text] format. The multiple RNA structure comparison problem is NP-hard in its general formulation...
October 19, 2017: Journal of Bioinformatics and Computational Biology
A Sreeja, K P Vinayan
In complex disorders, collaborative role of several genes accounts for the multitude of symptoms and the discovery of molecular mechanisms requires proper understanding of pertinent genes. Majority of the recent techniques utilize either single information or consolidate the independent outlook from multiple knowledge sources for assisting the discovery of candidate genes. In any case, given that various sorts of heterogeneous sources are possibly significant for quality gene prioritization, every source bearing data not conveyed by another, we assert that a perfect strategy ought to give approaches to observe among them in a genuine integrative style that catches the degree of each, instead of utilizing a straightforward mix of sources...
October 9, 2017: Journal of Bioinformatics and Computational Biology
Mohammad Arifur Rahman, Nathan LaPierre, Huzefa Rangwala, Daniel Barbara
Metagenomics is the collective sequencing of co-existing microbial communities which are ubiquitous across various clinical and ecological environments. Due to the large volume and random short sequences (reads) obtained from community sequences, analysis of diversity, abundance and functions of different organisms within these communities are challenging tasks. We present a fast and scalable clustering algorithm for analyzing large-scale metagenome sequence data. Our approach achieves efficiency by partitioning the large number of sequence reads into groups (called canopies) using hashing...
October 9, 2017: Journal of Bioinformatics and Computational Biology
Tatsuya Akutsu
No abstract text is available yet for this article.
October 2017: Journal of Bioinformatics and Computational Biology
Dongdong Sun, Minghui Wang, Ao Li
Due to the importance of post-translational modifications (PTMs) in human health and diseases, PTMs are regularly reported in the biomedical literature. However, the continuing and rapid pace of expansion of this literature brings a huge challenge for researchers and database curators. Therefore, there is a pressing need to aid them in identifying relevant PTM information more efficiently by using a text mining system. So far, only a few web servers are available for mining information of a very limited number of PTMs, which are based on simple pattern matching or pre-defined rules...
October 2017: Journal of Bioinformatics and Computational Biology
Yanshuo Chu, Zhenxing Wang, Rongjie Wang, Ningyi Zhang, Jie Li, Yang Hu, Mingxiang Teng, Yadong Wang
Structural controllability is the generalization of traditional controllability for dynamical systems. During the last decade, interesting biological discoveries have been inferred by applied structural controllability analysis to biological networks. However, false positive/negative information (i.e. nodes and edges) widely exists in biological networks that documented in public data sources, which can hinder accurate analysis of structural controllability. In this study, we propose WDNfinder, a comprehensive analysis package that provides structural controllability with consideration of node connection strength in biological networks...
October 2017: Journal of Bioinformatics and Computational Biology
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